Drug spend is an untamed beast in the realm of forecasting. On one hand, we see a multitude of inflationary trends that vary by therapeutic class, drug, route of administration, patent status, etc. and are heavily influenced by government policies. On the other hand, we are experiencing an accelerating pipeline of expensive, specialty therapies that will eventually hit the market. In 2015, it cost over $12 billion to produce a revolutionary new Hep C medication, or $40 per American. To put this number into perspective, it equals the entire coffee market in the US.
The cost burden falls squarely on the shoulder of plans, employers, and unions, as well as average consumers. Everyone feels the pressure, yet no one knows exactly what’s coming and how to plan for it.
Joanne Chen explores how data science powers business at Truveris, a health IT startup disrupting the prescription benefits industry, and discusses Truveris’s OneRx National Drug Index, the first index that provides a real-time holistic view of prescription drug prices. In an effort to mitigate this uncertainty around drug pricing, Joanne led the development of a methodology that considers historical pricing records, therapeutic category, and pipeline insight of each drug to forecast the pharmacy spend on a drug-by-drug, plan-by-plan basis, and her team leverages 1.5 billion pharmacy claims that they process in-house.
Joanne and her team have introduced granularity and increased precision into the modeling frame in order to more accurately assess spend forecast as compared to traditional methodologies. By helping payers (like insurance companies and employers) better understand their drug spend, we not only provide them with insights that drive better budgetary decisions but also help them become smarter in the selection of pharmacy benefit management services. This results in material dollar savings to the payers. But the payer example is just one case out of many where predicative analytics brings insights, efficiency and savings to the pharmacy value chain. Joanne explains how this lesson can be taken beyond drug spend to address the pressing issue of high costs in health care.
Joanne Chen joined Truveris as the first data scientist of the company and built the data science practice leveraging 1.5 billion pharmacy claims. In her current role as the vice president of data science, her responsibilities include full life-cycle management of products and data-driven R&D efforts. Prior to joining Truveris, Joanne was a statistics professional at Liberty Mutual focusing on personalized and targeted distribution strategy of auto products. Joanne has a PhD degree from Harvard in evolutionary biology and a master’s degree in statistics.
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